code: def get_optimizer(learning_rate=0.1):
      """Returns optimizer to use."""
      # The learning_rate is overwritten at the beginning of each step by
      # callback.
      return gradient_descent_v2.SGD(
          learning_rate=learning_rate, momentum=0.9
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  import numpy
  import tensorflow
  from tensorflow.python.keras.optimizer_v2 import gradient_descent
  from utils.flags import core
  from utils.misc import keras_utils
label_desc: Use image node_id 2 for calling a global function with example usage: get_optimizer(learning_rate) and returns: gradient_descent_v2